| Literature DB >> 34849886 |
Ole F Christensen1, Vinzent Börner1, Luis Varona2, Andres Legarra3.
Abstract
In animal and plant breeding and genetics, there has been an increasing interest in intermediate omics traits, such as metabolomics and transcriptomics, which mediate the effect of genetics on the phenotype of interest. For inclusion of such intermediate traits into a genetic evaluation system, there is a need for a statistical model that integrates phenotypes, genotypes, pedigree, and omics traits, and a need for associated computational methods that provide estimated breeding values. In this paper, a joint model for phenotypes and omics data is presented, and a formula for the breeding values on individuals is derived. For complete omics data, three equivalent methods for best linear unbiased prediction of breeding values are presented. In all three cases, this requires solving two mixed model equation systems. Estimation of parameters using restricted maximum likelihood is also presented. For incomplete omics data, extensions of two of these methods are presented, where in both cases, the extension consists of extending an omics-related similarity matrix to incorporate individuals without omics data. The methods are illustrated using a simulated data set.Entities:
Keywords: GenPred; Genomic Prediction; Shared Data Resource; breeding value; genetic evaluation; metabolomics; mixed model equations; single-step method; transcriptomics
Mesh:
Year: 2021 PMID: 34849886 PMCID: PMC8633135 DOI: 10.1093/genetics/iyab130
Source DB: PubMed Journal: Genetics ISSN: 0016-6731 Impact factor: 4.402